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Article

Electric Field-Coupled Micro/Nano Aeration Biofilter for Rural Sewage Treatment: Performance and Bacterial Community Analysis

by
Tongxuan Zhu
1,2,
Jinlei Li
1,2,
Yungen Liu
1,2,*,
Silin Yang
2,3,
Junlin Zhu
2,
Pengcheng Guo
2 and
Qi Wang
1,2,*
1
College of Soil and Water Conservation, Southwest Forestry University, Kunming 650224, China
2
Key Laboratory of Ecological Environment Evolution and Pollution Control in Mountainous & Rural Areas of Yunnan Province, Kunming 650224, China
3
Zhanyi Karst Ecosystem Observation and Research Station, Kunming 650224, China
*
Authors to whom correspondence should be addressed.
Sustainability 2025, 17(18), 8489; https://doi.org/10.3390/su17188489
Submission received: 17 August 2025 / Revised: 11 September 2025 / Accepted: 13 September 2025 / Published: 22 September 2025
(This article belongs to the Section Sustainable Water Management)
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Versions Notes

Abstract

The escalating demand for rural domestic wastewater treatment necessitates environmentally sustainable and cost-effective technologies. This study investigated the enhancement of a micro/nano aeration biofilter (MABF) through electric field coupling (E-MABF), evaluating pollutant removal efficacy and associated bacterial community dynamics. The results showed that the electric field significantly enhanced removal efficiency with respect to total phosphorus (TP), phosphate (PO43−-P), ammonium nitrogen (NH4+-N), and chemical oxygen demand (COD) (p < 0.05). The TP, PO43−-P, NH4+-N, and COD removal efficiencies for E-MABF reached 89.79%, 88.69%, 57.29%, and 57.96%, significantly exceeding those of MABF (26.50%,33.41%, 35.49%, and 45.75%). Electric field application markedly altered bacterial diversity and community composition. Core phyla, including Pseudomonadota, Chloroflexota, and Cyanobacteriota, exhibited significant positive correlations with pollutant removal efficiencies, indicating electric field facilitation of functional bacterial enrichment. KEGG pathway analysis suggested that electric field stimulation potentially enhanced metabolic functions, particularly in terpenoid and polyketide metabolism, and xenobiotics biodegradation. The Mantel’s test and structural equation model identified dominant bacterial composition as the primary factor influencing pollutant removal, followed by microenvironmental indicators and bacterial diversity. These findings elucidate the mechanisms underpinning the electric field augmentation of micro/nano aeration biofilter performance and provide a foundation for future research.

1. Introduction

With rapid global economic and population growth, water scarcity and aquatic environmental pollution have emerged as major challenges to sustainable development [1]. In China, the direct discharge of untreated domestic sewage in some rural areas has led to deteriorating water quality in lakes, rivers, and groundwater, disrupting the aquatic ecological balance and threatening public health [2,3]. In recent years, the advancement of the Rural Revitalization Strategy has driven increasingly stringent requirements for improving rural living environments and enhancing domestic sewage management in rural areas. Compared to urban domestic wastewater management, wastewater collection and treatment in rural areas pose greater challenges. In rural China, factors including dispersed populations, complex topography, significant fluctuations in water quality and quantity, and difficulties in sewer network construction render centralized treatment systems inapplicable [4,5]. Consequently, it is imperative to develop high-efficiency and high-performance process technologies that meet the requirements for decentralized treatment of rural domestic wastewater. While small-scale biofilters filled with high-permeability media are thought to be a viable solution, issues such as suboptimal treatment performance and operational instability persist, indicating that they do not fully align with rural requirements.
Currently, researchers have proposed multiple strategies, including, but not limited to, continuous aeration, supplemental carbon source addition, and the modification of packing materials. These approaches have been successfully implemented for the improvement of pollutant removal by enhancing dissolved oxygen (DO), carbon source supply, and the adsorption performance of packing materials. For instance, Li et al. [6] employed intensive aeration to induce oxidative reactions within the filter media, achieving rapid and deep autotrophic nitrogen removal. Separately, Zhao et al. [7] addressed carbon source deficiency in rural wastewater treatment under low carbon-to-nitrogen (C/N) ratios by incorporating Arundo donax into biofilter. Li et al. [8] employed a co-precipitation technique to modify quartz sand, achieving a 260.26% increase in specific surface area, which enhanced its suitability for the adhesion of microorganisms. Although strategies like continuous aeration, supplemental carbon addition, and media modification effectively enhance pollutant removal efficiency, they introduce some issues: continuous aeration increases energy consumption, media modification elevates construction costs, and carbon supplementation carries risks of fluctuating carbon release and secondary contamination. Consequently, developing environmentally sound and economically sustainable optimization approaches for biological filters has become imperative.
Micro/nano bubbles (MNBs), characterized by enhanced stability, superior gas dissolution efficiency, and high gas–liquid mass transfer rates [9], circumvent the high energy consumption associated with prolonged conventional aeration [10]. Xiao et al. [11] integrated MNB aeration with biological filters, optimizing DO distribution along the filtration path and enhancing microbial colonization, thereby demonstrating positive impacts on biofilter performance. Due to its advantages of low cost, operational simplicity, and elimination of chemical additives, the electro-field has been widely adopted as an enhanced ecological technology in biofilters. The combination of electric fields and biofilters has both the cost advantages of biodegradation and the high efficiency of electric fields. Furthermore, it leverages the advantages of microbially mediated redox reactions, enabling electroactive bacteria to drive the electrolytic oxidation of nitrogen, phosphorus, and organic contaminants. In addition, the abundant packing media in biofilters provide ample attachment sites for microorganisms. The electric field alters the activity and community composition of the attached microorganisms [12]. Electric field-coupled biofilters employ multiple pollutant degradation mechanisms owing to their diverse configurations, including adsorption, microelectrolysis, and biodegradation, thereby enhancing pollutant removal efficiency through synergistic action [13]. In summary, these findings demonstrate that both micro/nano aeration and electric fields enhance biofilter treatment performance. Supported by robust theoretical foundations, they represent effective strategies for improving pollutant removal efficiency in biological filters. Although applications of electric fields and micro/nano aeration in wastewater treatment are expanding, research on electric fields combined with micro/nano aerated biological filters, and particularly their underlying mechanisms, remains limited. Further investigation is required to elucidate the interaction mechanisms governing pollutant removal in electric field-coupled micro/nano aeration biofilter.
Therefore, this study constructed a micro/nano aeration biofilter (MABF) system and an electric field-coupled micro/nano aeration biofilter (E-MABF) system. The main objectives were (1) to evaluate the impact of electric field integration on pollutant removal efficiency in micro/nano aerated biological filters; (2) to investigate the effects of electric fields on bacterial community structure and diversity; and (3) to elucidate the influence of electric fields on the potential functions of microorganisms within micro/nano aerated biological filters.

2. Materials and Methods

2.1. Experimental Apparatus Setup and Operation

The micro/nano aeration biofilter (MABF) system and electric field-coupled micro/nano aeration biofilter (E-MABF) system (50 × 50 × 60 cm) were used in our study. The E-MABF system is shown in Figure 1. The E-MABF employed a stratified media configuration: a 10 cm basal stratum of volcanic rock (12–15 mm particle diameter); an intermediate 10 cm layer of ceramsite (10–13 mm particle diameter); and a 10 cm surface stratum of zeolite (5–6 mm particle diameter). In the E-MABF system, electric field enhancement was implemented by embedding graphite plates (5 mm × 40 cm × 30 cm) within the packing media layer, with an inter-electrode spacing of 20 cm. The system operated at 25 V and 270 mA, powered by a DC currant supply. The electrode terminals were interfaced via diameter copper conductors to regulate voltage for the E-MABF system operation. In the control group MABF, no electric fields enhancement measures are added, while the rest remains unchanged. The system water flow was driven by a micro/nano bubble generator, which drew water from a storage tank. After the micro/nano bubbles were mixed within the generator, the water was transferred to a stabilization tank. Subsequently, a peristaltic pump was used to pump the wastewater from the stabilization tank into the biofilter. The wastewater entered from the bottom of the biofilter and exited from the top. The hydraulic retention time (HRT) was defined as the contact time between the wastewater and the filter media inside the biofilter. Based on previous studies, HRT was set to 12 h, 24 h, and 36 h. Upon completion of the set HRT periods, water samples were collected from the outlet at the top of the biofilter. The inoculated sludge for the two systems was obtained from the sewage treatment plant at Southwest Forestry University. The test water was sourced from the effluent of the regulation pond of the same plant.

2.2. Water Sample Collection and Analysis Method

After achieving 30 days of stable operation, the experiment was initiated with a continuous feeding mode. The system maintained a single-cycle treatment capacity of 100 L, where hydraulic retention time (HRT) was controlled at 12 h, 24 h, and 36 h through precise flow rate regulation via peristaltic pumps. After system operation, water samples were collected from the designated sampling outlet. Each sample (500 mL) was analyzed immediately after collection, and the process was repeated three times. Routine water quality indicators, including total phosphorus (TP), phosphate (PO43−-P), ammonia nitrogen (NH4+-N), and chemical oxygen demand (COD), were determined in the laboratory following standardized methods. TP, PO43−-P, and NH4+-N were determined by a UV-6100 series UV–visible spectrophotometer, while COD analysis was performed with a HACH DR300 spectrophotometer. Dissolved oxygen (DO), oxidation-reduction potential (ORP), electrical conductivity (EC), and pH were measured via on-site measurements during each sampling event using a HACH HQ30d portable multi-parameter water quality analyzer.

2.3. Microbiological Analytical Methods

At the end of the experimental operation period, in order to study the community structure of bacterial distribution in MABF and E-MABF systems, mixed substrate samples (50 g each) were collected into sterilized beakers. Ultrasonic cleaning was performed for 10 min using ultrapure water to dislodge biofilms. The suspended biofilm was transferred into sterilized centrifuge tubes and centrifuged at 3000 r for 5 min. The pellet was transferred to a 2 mL sterilized centrifuge tube and stored in a dry ice container before shipment to Biozeron Biotechnology Co., Ltd. (Shanghai, China) for sequencing. The V3–V4 hypervariable regions of the 16S rRNA gene were amplified using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). High-throughput sequencing was conducted on the Illumina MiSeq platform. The phylogenetic affiliation of each 16S rRNA gene sequence was analyzed by the uCLUST algorithm against the Silva (SSU138.2)16S rRNA database using a confidence threshold of 80%. Raw sequences were quality-filtered, denoised, and clustered into operational taxonomic units (OTUs) at 97% similarity. Bacterial community composition was statistically analyzed across hierarchical levels.

2.4. Statistical Analysis

Experimental data were conducted utilizing Microsoft Excel 2019 and IBM SPSS Statistics 19.0. The data were presented as mean values ± standard deviations and assessed for significant differences using one-way ANOVA. Figures illustrating water quality parameters under different hydraulic retention times (HRTs), and microbial functional potential predictions (KEGG) were generated using Origin Pro 2021. Microbial community composition was analyzed and visualized via the Biozeron online platform. We calculated alpha diversity using Mothur v.1.21.1, and beta diversity was analyzed using was performed using Euclidean distance matrix to principal component analysis. The linear discriminant effect size analysis (LEfSe) was performed using the Wekemo Bioincloud platform. Correlation heatmaps were subsequently constructed on ChiPlot based on SPSS analytical outputs. Partial least squares path modeling (PLS-SEM) with the “plspm” package was used to perform path analysis based on pollutant removal.

3. Results and Discussion

3.1. Overall Pollutant Removal Performance

3.1.1. Phosphorus Removal Performance

Hydraulic retention time (HRT) significantly influenced pollutant removal efficiency (p < 0.05). The effects of different HRTs (12 h, 24 h, and 36 h) on TP and PO43−-P removal in the two systems are illustrated in Figure 2a,b. Compared to HRTs of 12 h and 24 h, both systems achieved optimal performance at 36 h. The average influent TP concentration was 5.34 mg/L, with the effluent concentrations of the MABF and E-MABF systems being 4.28 mg/L and 0.59 mg/L, respectively. The average influent PO43−-P concentration was 5.08 mg/L, and that of the MABF and E-MABF systems was 3.81 mg/L and 0.41 mg/L, respectively. Compared to the MABF system, the E-MABF system demonstrated enhanced removal efficiencies for TP and PO43−-P by 63.29% and 60.24%, respectively. Prolonging HRT significantly improved TP and PO43−-P removal in the E-MABF system (p < 0.05). When HRT was extended from 12 h to 36 h, the removal efficiencies increased by 12.42% and 8.28%. This was because the substrates of the two systems were composed of zeolite, ceramsite, and volcanic stone. As their surfaces were relatively rough and had multiple layered structures with microvoids, the substrates exhibited high adsorption capacity. Additionally, active Fe+ and exchangeable Al+ in the substrates could rapidly adsorb pollutants [14]. With the extension of HRT, the contact duration between the substrate and pollutants increased, reducing the scouring rate of wastewater on the biofilm and making the biofilm less prone to detachment. The removal efficiency of TP in the E-MABF system was consistently higher than that in the MABF system, suggesting that the E-MABF system exhibited better phosphorus removal performance. This enhanced removal efficiency was attributed to the electrochemical process—specifically the fact that the Fe2+ and Fe3+ generated by the electrodes likely formed complexes with PO43− in the wastewater [15] and reacted with OH− in the water to produce colloidal substances such as Fe (OH)2 or Fe (OH)3 [16], thereby achieving effective phosphate removal. The results of the present study indicate that the appropriate extension of HRT significantly enhanced the removal performance of both the MABF and E-MABF systems. Additionally, the introduction of an electric field further improved the phosphorus removal efficiency of the system.

3.1.2. Nitrogen Removal Performance

Figure 2c shows the NH4+-N removal efficiency of the MABF and E-MABF systems. Both systems achieved the highest average removal rates at 36 h, with average effluent concentrations of 35.49 mg/L and 26.77 mg/L, respectively. Compared with the MABF system, the E-MABF system exhibited a 13.9% improvement in NH4+-N removal efficiency. When HRT was extended from 12 h to 36 h, the removal rates of NH4+-N in the MABF and E-MABF systems increased by 26.45% and 23.91%, respectively. The result suggested that the main influencing factor of NH4+-N removal was HRT, which was consistent with previous research findings [17]. The denitrification pathways of both systems were traditional biological denitrification, namely, nitrification and denitrification reactions. In both systems, the substrates were natural materials that not only enabled ion exchange with NH4+ [18] but also provided favorable conditions for the attachment of nitrifying bacteria. The significant enhancement in NH4+-N removal efficiency for the MABF and E-MABF systems with prolonged HRT (p < 0.05) indicated that when HRT was sufficient, an adequate supply of electron donors in the systems could better participate in denitrification processes. In the E-MABF system, the introduction of an electric field enabled electrolysis to not only improve the activity of denitrifying bacteria but also generate organic matter and H2 as electron donors, which promoted electron transfer activity [19]. Thereby, the denitrification efficiency of denitrifying bacteria was enhanced, leading to better NH4+-N removal performance. Meanwhile, under the action of the electric field, the substrate underwent microelectrolysis to generate Al3+, which formed Al (OH)3 colloids in water [20] to achieve adsorption of NH4+-N. Additionally, an oxygen concentration gradient existed within both systems, enabling simultaneous nitrification and denitrification processes and effectively facilitating the conversion of NH4+-N. These experimental results further indicated that the introduction of an electric field effectively enhanced the synergy between nitrification and denitrification in the system.

3.1.3. Organic Matter Removal Performance

Figure 2d demonstrates the COD removal efficiency of the MABF and E-MABF systems. Compared with HRTs of 12 h and 24 h, both systems achieved the highest average removal rates at an HRT of 36 h, with average effluent concentrations of 128.91 mg/L and 99.83 mg/L, respectively. The COD removal efficiency of the E-MABF system was 12.24% higher than that of the MABF system. When the HRT was extended from 12 h to 36 h, the COD removal efficiency of the MABF and E-MABF systems increased significantly (p < 0.05), with the removal rates improving by 10.26% and 14.69%, respectively. This was because the prolonged contact reaction time facilitated heterotrophic bacteria’s utilization of EPS as a carbon and energy source under starvation conditions to decompose macromolecular organic matter [21]. In both systems, micro/nano bubbles played a significant role in organic matter removal. A portion of the micro/nano bubbles aggregated into larger bubbles that rapidly ascended and burst at the water surface, effectively stripping volatile organic compounds from the aqueous phase [22]. Concurrently, other micro/nano bubbles collapsed during ascent due to shrinkage, generating highly oxidative hydroxyl radicals. These radicals degraded organic pollutants through strong oxidation mechanisms [9]. The E-MABF system demonstrated superior organic matter treatment performance, which could be attributed to the integration of an electric field. On one hand, the electric field enhanced the effective removal of COD, which was consistent with the research findings reported by Zhang et al. (2024) [23]. This may be attributed to the enhanced activity of the microorganisms attached to the substrate, boosting their metabolic capacity [24]. Meanwhile, the electric field induced the production of more unsaturated fatty acids, thereby increasing dehydrogenase activity [25]. On the other hand, the substrate underwent electrochemical reactions under the electric field, generating substantial amounts of active [H] and Fe2+. These reactive species converted macromolecular refractory organic compounds into degradable small-molecule organics, making them more readily accessible for bacterial utilization [23]. In conclusion, the introduction of an electric field facilitated the effective removal of COD.

3.1.4. Changes in Microenvironmental Indicators

Microenvironmental indicators, such as ORP, DO, pH, and EC, are key factors influencing bacterial activity, organic matter degradation, and the denitrification and phosphorus removal efficiency within the systems. Changes in the microenvironmental indicators of effluent water quality under different HRTs in the MABF and E-MABF systems are shown in Figure 3. The influent ORP was maintained between −185 and −172 mV, and lower ORP values indicated strong reducing conditions. The effluent ORP of the E-MABF system increased significantly (p < 0.05), which was attributed to the oxidation of mineral ions released from electrodes and substrates by the functional bacteria in the system. This oxidation process caused the ORP to rise, reducing the pressure within the system and promoting the metabolism of facultative microorganisms [26]. The influent DO ranged from 1.67 to 2.85 mg/L. Elevated DO levels favored the proliferation of nitrifying bacteria, thereby promoting the conversion of NH4+-N. As the system operated, continuous DO consumption gradually created a low-oxygen environment, which triggered an increase in photosynthetic bacterial activity. Despite 36 h of continuous operation, anaerobic conditions did not develop in either the MABF or the E-MABF system. This resilience is attributed to the high oxygen transfer efficiency of micro/nano bubbles, which facilitated continuous oxygen dissolution at the gas–liquid interface [9], sustaining elevated DO concentrations throughout the operational period. In the E-MABF system, the effluent DO concentration was observed to increase, which was attributed to two factors: the electrolysis process generated a large number of reactive oxygen ions, and the effluent outlet was located at the top of the system, where atmospheric oxygen enrichment occurred [27], thereby providing an adequate supply of oxygen to the system to some extent. Li et al. [28] found that the synergistic regulation of ORP and DO can promote the synergy between endogenous denitrification and denitrifying phosphorus removal. The ion exchange between the substrate and water caused continuous changes in pH and EC within the systems. The effluent EC values of both systems decreased, indicating good capture efficiency for dissolved ions. Studies have shown that a slightly alkaline pH (7–8) in water bodies promotes the growth and proliferation of microorganisms [28]. During nitrogen and phosphorus removal, the hydrolysis of iron ions consumes alkalinity, potentially lowering pH. However, in the E-MABF system, effluent pH increased significantly compared to influent pH (p < 0.05). This phenomenon is consistent with the research findings reported by Mei et al. [27]. This is because of the cathodic consumption of H+ ions, which offset alkalinity depletion while generating -OH, thereby preventing pH decline and maintaining favorable conditions for bacterial activity [29]. Therefore, changes in HRT affect the microenvironmental parameters within the system, thereby influencing the bacterial living environment and pollutant purification efficiency.

3.2. Analysis of Community Abundance and Diversity

As shown in Figure 4a, the rarefaction curve was employed to assess the sequencing depth and sample size saturation. When the effective sequences of experimental samples exceeded 27,500, the curve reached a plateau, indicating sufficient sequencing coverage to reliably reflect the true bacterial community composition. Table 1 presents the bacterial OTUs (Operational Taxonomic Units), richness, and diversity measured in the MABF and E-MABF systems. The average number of OTUs in the MABF and E-MABF systems was 4575 and 6275, respectively. Overall, the E-MABF system exhibited higher bacterial community richness compared to the MABF system. Additionally, the two systems shared 3303 OTUs, indicating substantial differences in bacterial community composition between them. The Chao and ACE indices reflect bacterial community richness, while the Shannon and Simpson indices characterize bacterial diversity [30]. Compared to the MABF system, the E-MABF system demonstrated enhanced bacterial richness and diversity. This suggested that the electrical field application influenced bacterial growth, metabolism, and reproduction rates. These findings indicate that the electrical field exerted a positive effect on promoting bacterial proliferation and enhancing community diversity; further, the superior treatment performance of the E-MABF system could be attributed to enhanced bacterial diversity. Furthermore, principal component analysis (PCA) was conducted to evaluate the similarity between the two systems (Figure 4b). Samples from the E-MABF and MABF systems exhibited distinct clustering patterns, demonstrating significant differences in β-diversity between the systems. The contribution rates of PCA1 and PCA2 were 75.9% and 14.88%, respectively. Samples from the MABF system exhibited a relatively dispersed distribution with distinct bacterial community profiles, whereas samples from the E-MABF system showed clustered patterns and highly similar bacterial communities. Furthermore, it demonstrates that the electric field significantly alters the bacterial community structure, thus enhancing diversity.

3.3. Composition of Bacterial Community Structure

At the phylum level, Pseudomonadota, Chloroflexota, Bacteroidota, and Thermodesulfobacteriota were the dominant phyla, with their average relative abundances all exceeding 10% (Figure 5a). In the E-MABF system, the relative abundance of Pseudomonadota was 27.98%—significantly higher than that in the MABF system (Figure A1; p < 0.05). Pseudomonadota is recognized as a dominant phylum in many membrane bioreactors and wastewater treatment plants, serving as functional species for pollutant transformation and removal, with nitrogen and phosphorus removal capabilities, as well as the ability to degrade a wide range of organic compounds [31]. Pseudomonadota encompasses various electrochemically active bacteria, where the external electric field stimulates extracellular electron transfer [32]. Consequently, a significant increase in the relative abundance of Pseudomonadota was observed in the E-MABF system. In the correlation analysis (Figure 5b), the relative abundance of Pseudomonadota showed significant positive correlations with TP, PO43−-P, and COD (p < 0.05). This explains the higher removal efficiencies of TP, PO43−-P, and COD observed in the E-MABF system. Chloroflexota acts as a structural framework and carrier facilitating microbial aggregation and growth [33]. Compared to the MABF system, its abundance increased in the E-MABF, and although this difference was not statistically significant (p > 0.05), it nonetheless indicates that electric field exposure does not negatively impact Chloroflexota abundance. Furthermore, our study revealed a positive correlation between Chloroflexota and NH4+-N, consistent with its identification as an ammonifying bacterium involved in NH4+-N transformation during wastewater treatment [29,34]. Bacteroidota is recognized for its ability to decompose diverse complex organic compounds. In the E-MABF system, its relative abundance was 10.13%, which is significantly reduced compared to the MABF system (19.45%) (p < 0.05). Nevertheless, the relative abundance of Bacteroidota in E-MABF remained relatively high (>10%). Bacteroidota facilitates the denitrification process by producing organic acids through fermentation, which act as electron donors [35]. Thermodesulfobacteriota, a strictly anaerobic sulfate-reducing bacterium, decomposes organic matter by utilizing compounds such as lactate or pyruvate from wastewater as electron donors under anaerobic conditions [36]. Bacteroidota and Thermodesulfobacteriota both exhibited significant negative correlations with DO concentration (p < 0.05). The above analysis (Section 3.1.4) showed that the electric field increases DO levels in wastewater, thereby accounting for the decreased relative abundances of Bacteroidota and Thermodesulfobacteriota in the E-MABF system. This observation aligns with findings reported by Zhou et al. [37] and Hu et al. [38]. Notably, phyla that had low relative abundance (<1%) in the MABF system, such as Cyanobacteriota (0.51%) and Gemmatimonadota (0.22%), were substantially enriched in the E-MABF system under electric field exposure, reaching relative abundances of 9.89% and 1.08%, respectively. Cyanobacteriota, i.e., photosynthetic bacteria utilizing nutrients such as nitrogen and phosphorus to sustain their metabolism [39], contribute to N and P removal while simultaneously generating O2 through photosynthesis. Their relative abundance indicated significant positive correlations with TP and PO43--P removal efficiencies (p < 0.05). The relative abundance of Gemmatimonadota indicated a significant positive correlation with NH4+-N removal efficiency (p < 0.05), which aligns with its established role in nitrogen metabolic transformation during wastewater treatment [40]. Thus, the introduction of an electric field substantially augmented the abundance of functional bacteria, indicating that the removal of TP, PO43−-P, NH4+-N, and COD in the E-MABF system was primarily microbially mediated.
At the genus level (Figure 5c), the dominant genera in the MABF system were Longilinea (8.57%), WCHB1-32 (8.40%), Smithella (6.03%), and Chlorobium (4.72%). After electric field application, the dominant genera shifted significantly to GeminocystisPCC-6308 (5.04%), Longilinea (3.18%), Denitratisoma (2.44%), Lentimicrobium (2.20%), and WCHB1-32 (2.05%) in the E-MABF system. This restructuring indicates substantial electric field-induced alterations in bacterial community composition, with these genera demonstrating enhanced adaptability to the electro-stimulated environment. Geminocystis PCC-6308, a filamentous cyanobacterium within Cyanobacteriota, utilizes nutrients such as N and P to sustain its growth and proliferation. It typically performs polyphosphate cycling [41]. The relative abundance of Geminocystis PCC-6308 demonstrated significant positive correlations with TP, PO43−-P and NH4+-N removal efficiencies (p < 0.05) (Figure 5d). Its emergence as a dominant genus in the E-MABF system aligns with the aforementioned significant increase in Cyanobacteriota relative abundance. Denitratisoma, an anaerobic ammonifying bacterium within Pseudomonadota responsible for denitrification, exhibits high-efficiency nitrogen removal capabilities [42]. Its relative abundance demonstrated a significant positive correlation with NH4+-N removal efficiency (p < 0.05). The electric field likely facilitated Denitratisoma enrichment through accelerated Fe+ generation from electrodes, as iron serves as an essential element for anaerobic ammonifying bacteria growth. The relative abundance of Lentimicrobium exhibited a significant positive correlation with NH4+-N removal efficiencies (p < 0.05), consistent with the metabolic capability of Lentimicrobium to utilize nitrate as an electron acceptor for nitrogen removal. [43]. Both WCHB1-32 and Longilinea demonstrate hydrolytic acidification and acid production capabilities, enabling efficient carbohydrate metabolism [44] and organic matter degradation [45]. Therefore, the superior contaminant removal performance of the E-MABF system is highly likely attributable to the enrichment of these functional bacteria, which collectively enhance treatment efficacy.

3.4. Bacterial Communities with Significant Differences

To further investigate the divergences between the MABF and E-MABF systems, linear discriminant analysis effect size (LEfSe) analysis was performed (Figure 6). The results revealed that the electric field exerted inhibitory effects on Smithella, Chlorobium, WCHB1-32, Syntrophus, and Desulfomicrobium, while demonstrating an enrichment effect on Geminocystis PCC-6308, Lentimicrobium, Leptolinea, RBG-16-58-14, Nitrospira, Sulfuritalea, Ignavibacterium, Thiobacillus, and Rhodopseudomonas. Geminocystis PCC-6308 was the most divergent genus between the two systems. Sulfuritalea, Thiobacillus, and Rhodopseudomonas belong to Pseudomonadota. Sulfuritalea and Thiobacillus contribute significantly to nitrogen removal through heterotrophic growth-driven denitrification processes utilizing organic matter [46,47]. Rhodopseudomonas utilizes phosphate for growth and proliferation [48]. Its significant enrichment in the E-MABF system aligns with the previously observed increase in Pseudomonadota abundance, thereby providing a genus-level explanation for the positive correlations between Pseudomonadota’s relative abundance and TP, PO43−-P, NH4+-N, and COD removal. Notably, the E-MABF system exhibited a distinct capability to enrich Nitrospira. Nitrospira is a genus within Nitrospirota, which function as nitrite-oxidizing bacteria (NOB) with a nitrification capacity [49]. This enrichment likely contributes to the enhanced NH4+-N removal efficiency observed in the E-MABF system.

3.5. Potential Functions of Microbial Communities

Analyzing the composition of KEGG metabolic pathways, as well as their differences, is an effective means of studying the changes in the metabolic functions of microbial samples to adapt to their environment. Functional potential prediction was conducted via Tax4Fun integrated with the KEGG database (Figure 7). At KEGG Pathway Level 1 classification, metabolic processes dominated functional annotations, accounting for over 70% of the relative abundance. At KEGG Pathway Level 2, 27 pathways were identified. Notably, the relative abundances of lipid metabolism (3.91%), the metabolism of terpenoids and polyketides (2.33%), xenobiotics biodegradation and metabolism (2.91%) in the E-MABF system were all significantly higher than those in the MABF system (p < 0.05). These pathways are all associated with organic matter metabolism [50], with the metabolism of terpenoids and polyketides being particularly critical for anaerobic digestion processes [51]. The relative abundance of the biosynthesis of other secondary metabolites was significantly reduced (p < 0.05). This decrease is likely attributable to the electric field-induced enrichment of dominant functional bacteria, which ensures the efficient utilization of preferred substrates while suppressing the uptake and metabolism of non-preferred compounds [52]. Collectively, these findings further demonstrate that electric field stimulation positively modulates microbial metabolic pathways, thereby enhancing the contaminant removal performance of the E-MABF system.

3.6. Path Analysis of Impacts on Pollutant Removal

To further clarify the mechanisms of pollutant removal in the system, partial least squares path modeling (PLS-PM) was employed to analyze the relationships between dominant bacteria, bacterial diversity, microenvironmental indicators, and pollutant removal (Figure 8). Microenvironmental indicators exhibited significant positive direct effects on both pollutant removal and dominant bacteria (p < 0.05). Water quality parameters, such as pH, DO, etc., not only directly impact pollutant removal through enzyme reaction kinetics and chemical equilibrium [26] but also regulate microbial abundance and activity by altering the growth environment of dominant bacteria [53], thereby indirectly impairing contaminant removal efficiency. Both dominant bacteria and bacterial diversity exerted significant positive direct effects on pollutant removal, with the influence pathway of dominant bacteria being substantially stronger than that of bacterial diversity. The electric field significantly enhanced the abundance of functional bacteria responsible for nitrogen removal, phosphorus elimination, and organic matter decomposition, thereby improving pollutant removal. Furthermore, the dominant phyla, represented by Pseudomonadota and Chloroflexota, demonstrated significant positive correlations with the removal efficiencies of TP, PO43−-P, NH4+-N, and COD. These findings align with those of Ren et al. [53], confirming that microbial processes constitute the paramount mechanism for nutrient removal in biofilters. In summary, dominant bacteria emerged as the primary predictor exerting the greatest influence on pollutant removal, followed by microenvironmental indicators as the secondary predictor. Both demonstrated significant positive relationships with removal performance, whereas bacterial diversity exhibited no significant direct effect.

4. Conclusions

In summary, this study coupled the electric field with a micro/nano aeration biofilter (E-MABF), demonstrating that the electric fields were significantly enhanced, as well as stable removal efficiency for TP, PO43−-P, NH4+-N, and COD. In addition, the electric fields significantly affected the microenvironmental indicators of wastewater in the E-MABF system. Furthermore, the electric fields significantly influenced bacterial diversity and community structure. Collectively, the abundance of dominant bacteria was identified as the most critical variable governing pollutant removal efficiency, followed by microenvironmental indicators and dominant bacteria.

Author Contributions

T.Z., writing—original draft, methodology, formal analysis, investigation; J.L., investigation, data curation, formal analysis; Y.L., methodology supervision, data curation; S.Y., supervision, project administration; J.Z., supervision; P.G., investigation; Q.W., writing—review and editing, supervision, resources, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Key Project of Yunnan Province Science and Technology Department (202301AS070042; 202502AE090046).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

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Figure A1. The relative abundance of the dominant bacteria at the phylum level: (a):Pseudomonadota; (b) Chloroflexota; (c) Bacteroidota; (d) Thermodesulfobacteriota; (e) Cyanobacteriota; (f) Gemmatimonadota; One-way ANOVA results with Duncan test (p < 0.05). Different letters indicate significant differences in the main bacteria at the phylum level between the MABF and E-MABF systems.
Figure A1. The relative abundance of the dominant bacteria at the phylum level: (a):Pseudomonadota; (b) Chloroflexota; (c) Bacteroidota; (d) Thermodesulfobacteriota; (e) Cyanobacteriota; (f) Gemmatimonadota; One-way ANOVA results with Duncan test (p < 0.05). Different letters indicate significant differences in the main bacteria at the phylum level between the MABF and E-MABF systems.
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Figure 1. Device diagram of E-MABF systems.
Figure 1. Device diagram of E-MABF systems.
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Figure 2. The treatment performance of the MABF and E-MABF systems: (a) TP; (b) PO43−-P; (c) NH4+-N; (d) COD. Different letters indicate statistical differences among different outlet water concentrations (p < 0.05).
Figure 2. The treatment performance of the MABF and E-MABF systems: (a) TP; (b) PO43−-P; (c) NH4+-N; (d) COD. Different letters indicate statistical differences among different outlet water concentrations (p < 0.05).
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Figure 3. Microenvironmental changes in MABF and E-MABF systems: (a) oxidation-reduction potential (ORP); (b) dissolved oxygen (DO); (c) pH; and (d) conductivity (EC). Different letters indicate statistical differences among different inlet and outlet water concentrations (p < 0.05).
Figure 3. Microenvironmental changes in MABF and E-MABF systems: (a) oxidation-reduction potential (ORP); (b) dissolved oxygen (DO); (c) pH; and (d) conductivity (EC). Different letters indicate statistical differences among different inlet and outlet water concentrations (p < 0.05).
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Figure 4. Diversity of the bacterial community: (a) effective sequences of experimental samples; (b) principal component analysis (PCA).
Figure 4. Diversity of the bacterial community: (a) effective sequences of experimental samples; (b) principal component analysis (PCA).
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Figure 5. Community composition of bacteria at phylum (a) and gene (c) level and Pearson’s rank correlation matrix of bacteria at phylum (b) and gene (d) level. * indicates p < 0.05; ** indicates p < 0.01.
Figure 5. Community composition of bacteria at phylum (a) and gene (c) level and Pearson’s rank correlation matrix of bacteria at phylum (b) and gene (d) level. * indicates p < 0.05; ** indicates p < 0.01.
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Figure 6. LEfSe analysis of microbial communities in MABF and E-MABF systems: (a) cladogram; (b) LDA score distribution histogram (LDA score > 3.8).
Figure 6. LEfSe analysis of microbial communities in MABF and E-MABF systems: (a) cladogram; (b) LDA score distribution histogram (LDA score > 3.8).
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Figure 7. Potential microbial function profiles in the E-MABF and MABF systems. * indicates p < 0.05.
Figure 7. Potential microbial function profiles in the E-MABF and MABF systems. * indicates p < 0.05.
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Figure 8. Path analysis of impacts on pollutant removal. The red line indicates positive correlation, and the blue line indicates positive correlation. Solid lines indicate significant correlations, and dashed lines indicate non-significant correlations. * indicates p < 0.05; ** indicates p < 0.01.
Figure 8. Path analysis of impacts on pollutant removal. The red line indicates positive correlation, and the blue line indicates positive correlation. Solid lines indicate significant correlations, and dashed lines indicate non-significant correlations. * indicates p < 0.05; ** indicates p < 0.01.
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Table 1. Microbial community richness and diversity at different sampling sites in the two systems.
Table 1. Microbial community richness and diversity at different sampling sites in the two systems.
OTUsChaoACEShannonSimpson
MABF45753705.683996.686.420.99
E-MABF62754893.095351.286.910.98
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Zhu, T.; Li, J.; Liu, Y.; Yang, S.; Zhu, J.; Guo, P.; Wang, Q. Electric Field-Coupled Micro/Nano Aeration Biofilter for Rural Sewage Treatment: Performance and Bacterial Community Analysis. Sustainability 2025, 17, 8489. https://doi.org/10.3390/su17188489

AMA Style

Zhu T, Li J, Liu Y, Yang S, Zhu J, Guo P, Wang Q. Electric Field-Coupled Micro/Nano Aeration Biofilter for Rural Sewage Treatment: Performance and Bacterial Community Analysis. Sustainability. 2025; 17(18):8489. https://doi.org/10.3390/su17188489

Chicago/Turabian Style

Zhu, Tongxuan, Jinlei Li, Yungen Liu, Silin Yang, Junlin Zhu, Pengcheng Guo, and Qi Wang. 2025. "Electric Field-Coupled Micro/Nano Aeration Biofilter for Rural Sewage Treatment: Performance and Bacterial Community Analysis" Sustainability 17, no. 18: 8489. https://doi.org/10.3390/su17188489

APA Style

Zhu, T., Li, J., Liu, Y., Yang, S., Zhu, J., Guo, P., & Wang, Q. (2025). Electric Field-Coupled Micro/Nano Aeration Biofilter for Rural Sewage Treatment: Performance and Bacterial Community Analysis. Sustainability, 17(18), 8489. https://doi.org/10.3390/su17188489

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